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Updated: Jan 26, 2026

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
Published on: October 13, 2020
OpenMS - A platform for reproducible analysis of mass spectrometry data
Julianus Pfeuffer1, Timo Sachsenberg2, Oliver Alka2
1Applied Bioinformatics, Department for Computer Science, University of Tuebingen, Sand 14, 72076 Tuebingen, Germany; Center for Bioinformatics, University of Tuebingen, Sand 14, 72076 Tuebingen, Germany; Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany.
Background:
In recent years, several mass spectrometry-based omics technologies emerged to investigate qualitative and quantitative changes within thousands of biologically active components such as proteins, lipids and metabolites. The research enabled through these methods potentially contributes to the diagnosis and pathophysiology of human diseases as well as to the clarification of structures and interactions between biomolecules. Simultaneously, technological advances in the field of mass spectrometry leading to an ever increasing amount of data, demand high standards in efficiency, accuracy and reproducibility of potential analysis software.
Results:
This article presents the current state and ongoing developments in OpenMS, a versatile open-source framework aimed at enabling reproducible analyses of high-throughput mass spectrometry data. It provides implementations of frequently occurring processing operations on MS data through a clean application programming interface in C++ and Python. A collection of 185 tools and ready-made workflows for typical MS-based experiments enable convenient analyses for non-developers and facilitate reproducible research without losing flexibility.
Conclusions:
OpenMS will continue to increase its ease of use for developers as well as users with improved continuous integration/deployment strategies, regular trainings with updated training materials and multiple sources of support. The active developer community ensures the incorporation of new features to support state of the art research.
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